title: Predicting chronic obstructive pulmonary disease hospitalizations based on concurrent influenza activity.
abstract: Although influenza has been associated with chronic obstructive pulmonary disease (COPD) exacerbations, it is not clear the extent to which this association affects healthcare use in the United States. The first goal of this project was to determine to what extent the incidence of COPD hospitalizations is associated with seasonal influenza. Second, as a natural experiment, we used influenza activity to help predict COPD admissions during the 2009 H1N1 influenza pandemic. To do this, we identified all hospitalizations between 1998 and 2010 in the Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project (HCUP) during which a primary diagnosis of COPD was recorded. Separately, we identified all hospitalizations during which a diagnosis of influenza was recorded. We formulated time series regression models to investigate the association of monthly COPD admissions with influenza incidence. Finally, we applied these models, fit using 1998-2008 data, to forecast monthly COPD admissions during the 2009 pandemic. Based on time series regression models, a strong, significant association exists between concurrent influenza activity and incidence of COPD hospitalizations (p-value < 0.0001). The association is especially strong among older patients requiring mechanical ventilation. Use of influenza data to predict COPD admissions during the 2009 H1N1 pandemic reduced the mean-squared prediction error by 29.9%. We conclude that influenza activity is significantly associated with COPD hospitalizations in the United States and influenza activity can be exploited to more accurately forecast COPD admissions. Our results suggest that improvements in influenza surveillance, prevention, and treatment may decrease hospitalizations of patients diagnosed with COPD.
authors.affiliation: 1Department of Internal Medicine, University of Iowa , Iowa City, IA , USA.
authors.forename: Alicia K
authors.initials: AK
authors.lastname: Gerke
authors.forename: Fan
authors.initials: F
authors.lastname: Tang
authors.forename: Ming
authors.initials: M
authors.lastname: Yang
authors.forename: Eric D
authors.initials: ED
authors.lastname: Foster
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Cavanaugh
authors.forename: Philip M
authors.initials: PM
authors.lastname: Polgreen
mesh_terms: D000368:Aged; D018450:Disease Progression; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology*; D008875:Middle Aged; D029424:Pulmonary Disease, Chronic Obstructive / Q000453:epidemiology*; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods; D013997:Time Factors; D014481:United States / Q000453:epidemiology